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JDave vs unittest comparison of testing frameworks
What are the differences between JDave and unittest?

JDave

http://jdave.org/

unittest

https://docs.Python.org/3/library/unittest.html
Programming language

Java

Python

Category

Acceptance Testing

Unit Testing

General info

JDave is a BDD framework for Java

JDave is inspired by RSpec and integrates JMock 2 as mocking framework and Hamcrest as matching library. It uses JUnit adapter to launch JDave specifications. This way it is possible to have IDE, build tool and coverage tool support from day one.

unittest is a unit testing framework for Python

The unittest test framework is Python’s xUnit style framework. It is a standard module that is bundled with Python and supports the automation and aggregation of tests and common setup and shutdown code for them.
xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.

No

Yes

unittest is a xUnit style frameworkfor Python, it was previously called PyUnit.
Client-side
Allows testing code execution on the client, such as a web browser

Yes

Front-end behaviour can be tested with JDave

Yes

Front-end functionality and behaviour can be tested by unittest.
Server-side
Allows testing the bahovior of a server-side code

Yes

JDave can test server-side behaviour

Yes

Since the webserver funtionalities have their own features and each feature has its own functions, we can write tests with unittest to test each function
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

N/A

Yes

By use of the 'setUp()' function which is called to prepare the test fixture
Group fixtures
Allows defining a fixed, specific states of data for a group of tests (group-fixtures). This ensures specific environment for a given group of tests.

N/A

Yes

unittest allows you to group your initialization code into a setUp function and clean up code in a tearDown function
Generators
Supports data generators for tests. Data generators generate input data for test. The test is then run for each input data produced in this way.

N/A

Yes

unittest contains generator methods in the module 'unittest.TestCase'
Licence
Licence type governing the use and redistribution of the software

Apache License 2.0

MIT License

Mocks
Mocks are objects that simulate the behavior of real objects. Using mocks allows testing some part of the code in isolation (with other parts mocked when needed)

Yes

It integrates JMock 2 as mocking framework

Yes

Mocks are available from the library unittest.mock which allows you to replace parts of your system under test with mock objects
Grouping
Allows organizing tests in groups

Yes

Specifications can be grouped by tagging them with @Group annotation.

Yes

One can build suites either manually or use test discovery to build the suite automatically by scanning a directory
Other
Other useful information about the testing framework